Software Engineer - Data

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.

ABOUT THE ROLE:

At SpaceXAI, we are building AI systems that push the frontier of human knowledge and scientific discovery. High-quality data is fundamental to every stage of that mission. Our Data team is responsible for ensuring that the models are trained on the right data, in the right form, at the right quality, across every phase of the training lifecycle. This includes partnering closely with acquisition teams to identify where valuable data can be sourced, determining what data is needed to improve model performance, and building the production pipelines and systems that transform raw inputs into high-quality training data at scale. We work at the intersection of software, data, infrastructure, and machine learning to ensure our models train effectively and reliably.

As a Software Engineer on SpaceXAI's Data team, you will be responsible for developing applications that power data acquisition, preparation, training, quality evaluation, and delivery for model training. You will provide the ability to run training in a reliable, scalable and repeatable manner. You will also provide visibility on training status and data lineage. You will work closely with acquisition teams, ML engineers, and data engineers to build a reliable data pipeline to run training at scale. The ideal candidate combines strong software engineering fundamentals and excellent coding practices.

RESPONSIBILITIES:

• Develop a highly reliable and scalable enterprise data platform to orchestrate data acquisition, preparation, training, quality evaluation, and delivery for model training

• Create new features such as data lineage, visibility, and monitoring for end-to-end training that improve the quality of the data and model performance